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Who is winning global tech race? | The Express Tribune
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The Global AI Summit kicks off at the Saudi capital Riyadh, September 13, 2022. PHOTO:Twitter Al Arabiya
KARACHI:
“China is going to win the AI race.” The remark sent ripples through Silicon Valley and beyond when Jensen Huang, CEO of US chipmaking giant Nvidia, made it at an AI summit in London earlier this month. Huang, whose company dominates the global AI chip market, later softened his position, saying China is merely “nanoseconds behind America.”
But Greg Slabaugh, Professor of Computer Vision and AI at Queen Mary University of London, is convinced that China has “already won” the AI race. And he made a startling revelation to back up his claim: of all the papers presented at the 2025 International Conference on Computer Vision in Hawaii, half were authored by Chinese researchers – far outstripping the US at 17%. Factor in Chinese nationals working abroad, and the gap would widen even further.
Three years before Huang’s candid acknowledgement, the Australian Strategic Policy Institute had reported that China leads in 57 out of 64 critical technologies – from quantum sensors and AI to robotics and semiconductors – while the US maintains an edge in far fewer areas, such as biotechnology and aerospace. This marks a dramatic reversal from 2003 to 2007, when the US led in 60 of 64 technologies and China in just three. Beijing’s current dominance stems from a high-impact research ecosystem in which, in some fields, it holds something close to a near-monopoly.
This meteoric rise, especially in AI, couldn’t be stymied by US efforts to limit China’s access to advanced chips and manufacturing equipment, which were intended to maintain America’s edge in the sector. Unlike past advantages based on cheap labour or scale, China’s AI lead is structural, built on concerted strategy, coordinated investment, and an energy ecosystem optimised for massive computational growth.
The AI revolution is, at its core, a revolution of power – in both senses of the word. Training the largest data models requires a huge computing capacity, which is powered by electricity on a colossal scale. By the decade’s end, experts say, AI data centres could consume more power than some mid-sized nations. And China holds a decisive edge in this high-voltage contest. Its subsidised electricity, flexible regulation, and capacity to execute large-scale projects at rapid speed have led to the mushrooming of AI infrastructure nationwide. From data-centre clusters in Inner Mongolia to renewable-powered server farms in Sichuan, Beijing has built an energy foundation capable of sustaining AI’s exponential growth. On the contrary, US tech giants are increasingly hamstrung by a growing web of constraints. The American electricity grid is old and fragmented, creating logistical and regulatory bottlenecks. Microsoft has conceded that energy shortages are slowing the expansion of its data centre. Chinese authorities, meanwhile, have turned energy planning into a national security priority – integrating AI, cloud computing, and grid modernisation into one strategic blueprint.
While Western firms like OpenAI and Anthropic pursue closed, commercial AI models, Chinese developers have doubled down on open-weight systems – models whose trained parameters are freely available. The result has been an open-source explosion that is transforming global software development. Chinese open-source AI downloads have now surpassed those from the US, according to venture capital firm a16z. Companies such as DeepSeek, MiniMax, Z.ai, and Moonshot are releasing high-performance models at a fraction of US prices.
China’s innovation often lies not in raw capability, but in accessibility and cost efficiency. Airbnb CEO Brian Chesky recently revealed that his company had replaced OpenAI’s ChatGPT with Alibaba’s Qwen model, calling it “fast and cheap.” Chamath Palihapitiya, CEO of Social Capital, said his firm has switched to Moonshot’s Kimi K2, describing it as “way more performant” than American rivals.
Conflicting approaches are at play here. The United States, by its own admission, wants to maintain global leadership in AI to secure its economic competitiveness. China, on the other hand, pushes for democratisation of AI, promoting open cooperation, capacity building for developing nations, and an “AI for the public good.” With this approach, Beijing has flipped one of Washington’s strategic levers. American export controls – meant to slow Chinese progress by denying access to cutting-edge chips – have instead spurred Chinese firms to build leaner models that run on older hardware. “They’ve actually encouraged Chinese companies to be more resourceful,” said AI researcher Toby Walsh. “It’s exactly what happened with solar panels – constraints made them smarter and cheaper.”
The story doesn’t end there. One of the most consequential areas of Chinese dominance is remote sensing: the science of gathering data from a distance through satellites, drones, and advanced sensors. A recent global analysis of 126,000 peer-reviewed papers found that China produced nearly 47% of all remote sensing research between 2021 and 2023. The American share, which stood at 88% during the Cold War, has fallen to just 9%. The patent landscape tells the same story. Among the top 19 global patent filers in remote sensing between 2021 and 2023, Chinese institutions accounted for 62%. Why does this matter? Because remote sensing underpins nearly every next-gen technology – from self-driving cars and smart cities to climate modeling and precision agriculture. Whoever controls the sensors, data flows, and analytic algorithms effectively controls the informational foundation of modern economies.
That said, China’s leap was no accident. Since the early 2000s, Beijing has strategically targeted the field for heavy investment under national programmes like the “973 Plan,” pairing state funding with private enterprise. The result: a vast ecosystem of universities, startups, and ministries working in concert. The US, by contrast, has relied heavily on NASA and the private sector. But fragmented research funding, bureaucratic inertia, and inconsistent industrial policy have eroded its early lead. When one country produces nearly half of global output in a strategic domain, and controls most patents and funding, it is shaping the next generation of value chains.
China’s stratospheric rise extends far beyond data and algorithms. In sector after sector, Western companies find themselves being out-produced, out-priced, and out-innovated. In automobiles, Chinese brands are redefining global competition. In 2024, Chinese carmakers captured 7.4% of all passenger car sales in Europe, nearly doubling their share within a year. EV maker Leapmotor posted a staggering 7,000% jump in sales, while BYD and Chery continue their European expansion with EVs far more affordable than Western models. This is why Ford CEO Jim Farley recently issued a blunt warning: “They have enough production capacity in China to serve the entire North American market.”
The same dynamic plays out in wind power, where Chinese manufacturers like Goldwind, Envision, and Mingyang now occupy the top four global slots – pushing Western rivals Siemens Energy, GE, and Vestas down the rankings. Chinese turbines are up to 50% cheaper, thanks to economies of scale and domestic demand that dwarfs anything in Europe or the US.
Having said that, all is not lost for the West, particularly the US, which still dominates the premium end of AI, biotechnology, and aerospace. Yet Washington must rethink its approach: instead of trying to slow China’s rise through export controls and strategic containment, it should focus on large-scale investment in energy infrastructure, R&D, and education. At the same time, it needs to face the new reality.
The writer is an independent journalist with special interest in geoeconomics
Business
New Income Tax rules from 1 April 2026: 50% HRA exemption for Salaried employees in THESE cities may soon be a reality
New Delhi: Good news for salaried employees who are likely to benefit from a higher income tax exemption as the draft Income Tax Rules 2026 propose a major change in House Rent Allowance (HRA) deductions. If approved by Parliament, these changes may apply from April 1, 2026.
According to the draft Income-tax Rules, 2026, the government is proposing to expand the scope of higher HRA tax exemption under the old income-tax regime by extending it to more cities. The proposal aims to align tax relief with increased rental prices in rapidly expanding cities and evolving job trends.
New Income Tax: What is the proposed change?
Currently, salaried employees in Mumbai, Delhi, Kolkata and Chennai can claim an HRA tax exemption of up to 50 percent of their salary while those living in other cities can only claim an exemption of 40 percent. Under the draft rules, cities of Bengaluru, Hyderabad, Pune and Ahmedabad are proposed to be added to the 50 percent category.
New Income Tax: How will the exemption be determined?
According to the proposal, the method for computing HRA relief will remain the same. The exemption will be determined as the lowest of three figures which is the actual allowance received, the excess of rent paid over 10 percent of pay or a prescribed portion of salary linked to the employee’s city of residence.
New Income Tax: Why HRA matters?
HRA is a portion of an employee’s salary that an employer contributes to help cover house rent. Under the old tax regime, some part of HRA is not taxed which enables employees to save tax. HRA tax benefit is available only in the old tax regime and not in the new one. Even though the newer framework offers lower slab rates, only those employees who opt for the old system are eligible for the HRA exemption.
New Income Tax: What has govt proposed the changes?
The government has proposed the changes to update HRA norms in response to India’s changing economic landscape. In recent times, cities including Bengaluru, Hyderabad and Pune have drawn in a sizeable salaried population. The proposal also aims to align tax relief with higher rental prices in these rapidly expanding cities.
The final regulations will be forwarded to Parliament following assessment. If approved, these changes will apply from April 1, 2026.
Pakistan is preparing to repay about $1.3 billion in principal and interest on a maturing Eurobond in April 2026, as negotiations with the International Monetary Fund (IMF) approach under the country’s $7 billion reform programme.
As the IMF review mission prepares to arrive in Pakistan later this month, officials said the delegation will stay in Karachi for a couple of days before moving to Islamabad around March 2, 2026, for key discussions under the $7 billion Extended Fund Facility (EFF).
These talks are expected to focus on fiscal reforms, external financing and progress on structural benchmarks agreed under the program.
Officials indicated that the Ministry of Finance plans to launch Panda bonds shortly after the end of holidays in China in an effort to raise the first tranche of $250 million.
According to sources, there are indications of strong investor interest, with expectations of oversubscription for the bond issuance.
The government, officials said, repaid a $700 million Chinese commercial loan ahead of schedule to demonstrate its repayment capacity, while Chinese banks have reportedly assured refinancing within the ongoing fiscal year.
Pakistan is also engaged in negotiations with international commercial banks to secure an additional $500 million in fresh financing during the current fiscal cycle.
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Yotta Data Services to spend $2 billion to deploy Nvidia’s latest Blackwell chips in India, building one of Asia’s largest AI superclusters
Yotta Infrastructure’s Greater Noida data centre park (Photo Credit: Yotta’s website)
India’s data centre sector is entering a new era of scale. Yotta Data Services said Wednesday, February 18, that it will deploy Nvidia’s most-advanced artificial intelligence chips in a $2-billion project that will establish one of the largest AI computing hubs in Asia, positioning the country as a serious contender in the global race for AI infrastructure.
The investment centres on the first-ever deployment of Nvidia’s Blackwell B300 graphics processing units in India, to be housed at Yotta’s hyperscale campus in Noida, just outside New Delhi. The supercluster is expected to go live by August.
Anchoring the project is a four-year agreement with Nvidia valued at roughly $1 billion, under which the chipmaker will establish one of Asia-Pacific’s largest DGX Cloud clusters within Yotta’s infrastructure. Sunil Gupta, managing director and chief executive of Yotta, told The Economic Times that Nvidia will deploy approximately 10,300 GPUs through the arrangement to serve its global Asia-Pacific customers and run its own models and services. “Nvidia is creating one of Asia’s largest DGX Cloud clusters on our supercluster,” Gupta said.
The deal underscores a broader shift in how hyperscalers and chipmakers are approaching India. Global cloud providers, including Microsoft and Amazon, have been expanding AI data centre capacity in the country, drawn by surging demand for generative AI services and government pressure to localise advanced computing infrastructure, according to Reuters. Nvidia’s direct commitment within Yotta’s facility goes a step further, signalling confidence in India as a viable hub for serving enterprise AI workloads across the region.
A significant share of remaining capacity will be dedicated to India’s national AI Mission, which has received more than 500 applications from start-ups seeking affordable compute access. Gupta told The Economic Times that the expansion will increase the country’s compute capacity “by almost five to six times”, addressing what he described as enormous pressure on existing resources. The infrastructure will support state-backed Indian language model initiatives, including Bhashini, Sarvam, BharatGen and Soket, all aimed at building foundational AI models trained on Indian-language datasets.
Yotta currently holds around 10,000 advanced Nvidia GPUs, accounting for nearly 75% of India’s GPU compute capacity. With the new deployment, its total GPU count will rise from roughly 40,000 to more than 75,000 over the next two years.
The capital push is being funded through a combination of debt and equity. Speaking to CNBC-TV18, Gupta said the company is targeting a fundraise of close to $1 billion to support its current phase of GPU deployment. Yotta has already invested over $1.5 billion in infrastructure and expects to commit an additional $2 billion toward advanced chips. A pre-IPO equity round is underway, with the company aiming to enter public markets within the current financial year.
Yotta is part of Indian billionaire Niranjan Hiranandani’s real estate conglomerate and operates data centre campuses in Mumbai, Gujarat and near New Delhi. Additional capacity from its Mumbai facility will supplement the Noida supercluster.
The timing of the investment is notable. US export controls have reshaped global supply chains for advanced AI semiconductors, pushing technology firms to deepen partnerships in markets that remain accessible. India, which has cultivated strong ties with Washington and positioned itself as a neutral beneficiary of great-power competition in technology, has emerged as one of the cleaner plays for companies looking to expand AI compute outside China.
Speaking to CNBC-TV18, Gupta said that India’s AI ambitions are grounded in practical outcomes, with the goal of delivering impact across agriculture, healthcare, education and climate. He drew a comparison to the Unified Payments Interface, suggesting AI-led transformation could similarly reshape how services are delivered at scale across the country.
For Nvidia, the DGX Cloud anchor at Yotta is the latest in a string of sovereign and commercial AI infrastructure deals across Asia, as the company works to deepen its footprint ahead of any potential tightening of chip export restrictions.
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